多种调度模式下的光储电站经济性最优储能容量配置分析
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摘要
光储联合发电系统是促进大容量光伏电站集中并网的解决方案之一。因现阶段储能造价较高,所以合理配置储能容量是提高光储电站经济性的重要前提。该文对光储电站不同调度模式进行分析,从发电企业的角度出发以净收益最优为目标建立储能容量优化模型。模型中,结合电池循环寿命数据,建立电池损耗成本函数,定量计算储能实际运行成本,同时计及售电收益、考核费用,利用粒子群算法求解净收益最优时的储能容量,并通过多种方案对比,仿真验证模型有效性。最后对影响光储电站经济性的敏感因素进行分析,为光储电站在不同调度模式、不同市场环境下的储能容量选择提供参考信息。
Photovoltaic generation combined energy storage system is one of the solutions to enhance the capacity of centralized grid-connected PV power plant that interconnects grid. At the present stage,the cost of energy storage is high,and the rational allocatio n of energy storage capacity is an important prerequisite to improve the economy of the cogeneration system. In this paper,different scheduling modes of the cogeneration are analyzed,and the optimization model of energy storage capacity is established to maximize the net profit from the perspective of power generation enterprise. In the model,the function of battery loss cost is established combining with the battery cycle life data to calculate the actual battery operating costs quantitatively. Meanwhile,consider the electricity selling revenue and penalty cost to calculate the optimal energy storage capacity by particle swarm optimization(PSO)algorithm,and the validity of the model is verified by comparing the variety of the plans. Finally,the sensitive factors that affect the economy of the Photovoltaic power station combined energy storage system are analyzed,which provide reference information for the selection of the energy storage capacity in the future market environment.
Photovoltaic generation combined energy storage system is one of the solutions to enhance the capacity of centralized grid-connected PV power plant that interconnects grid. At the present stage,the cost of energy storage is high,and the rational allocatio n of energy storage capacity is an important prerequisite to improve the economy of the cogeneration system. In this paper,different scheduling modes of the cogeneration are analyzed,and the optimization model of energy storage capacity is established to maximize the net profit from the perspective of power generation enterprise. In the model,the function of battery loss cost is established combining with the battery cycle life data to calculate the actual battery operating costs quantitatively. Meanwhile,consider the electricity selling revenue and penalty cost to calculate the optimal energy storage capacity by particle swarm optimization(PSO)algorithm,and the validity of the model is verified by comparing the variety of the plans. Finally,the sensitive factors that affect the economy of the Photovoltaic power station combined energy storage system are analyzed,which provide reference information for the selection of the energy storage capacity in the future market environment.
引文
[1]吴克河,周欢,刘吉臻.大规模并网型风光储发电单元容量优化配置方法[J].太阳能学报,2015,26(12):2946—2953.[1]Wu Kehe,Zhou Huan,Liu Jizhen. Capacity allocation optimization method of large scale grid connected windPV-battery generation unit[J]. Acta Energiae Solaris Sinica,2015,26(12):2946—2953.
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[9]李碧辉,申洪,汤涌,等.风光储能联合发电系统储能容量对有功功率的影响及评价指标[J].电网技术,2011,35(4):123—128.[9]Li Bihui,Shen Hong,Tang Yong,et al. Impacts of energy storage capacity configuration of HPWS to active power characteristics and its relevant indices[J]. Power System Technology,2011,35(4):123—128.
[10]梁亮,李建林,惠东,等.大型风电场用储能装置容量的优化配置[J].高电压技术,2011,37(4):930—936.[10]Liang Liang,Li Jianlin,Hui Dong,et al. Optimization configuration for capacity of energy storage system in large-scale wind farm[J]. High Voltage Engineering,2011,37(4):930—936.
[11]冯江霞,梁军,张峰,等.考虑调度计划和运行经济性的风电场储能容量优化计算[J].电力系统自动化,2013,37(1):90—95.[11]Feng Jiangxia,Liang Jun,Zhang Feng,et al. An optimization calculation method of wind farm energy storage capacity[J]. Automation of Electric Power System,2013,37(1):90—95.
[12]姜书鹏,乔颖,徐飞,等.风储联合发电系统容量优化配置模型及敏感性分析[J].电力系统自动化,2013,37(20):16—21.[12]Jiang Shupeng,Qiao Ying,Xu Fei,et al. Capacity optimization and sensitivity analysis of cogeneration system of wind power and energy storage[J]. Automation of Electric Power Systems,2013,37(20):16—21.
[13]陆秋瑜,胡伟,闵勇,等.考虑时间相关性的风储系统多模式协调优化策略[J].电力系统自动化,2015,39(2):6—12.[13]Lu Qiuyu,Hu Wei,Min Yong,et al. A multi-pattern coordinated optimization strategy of wind power and energy storage system considering temporal dependence[J]. Automation of Electric Power System,2015,39(2):6—12.
[14]严干贵,冯晓东,李军徽,等.用于松弛调峰瓶颈的储能系统容量配置方法[J].中国电机工程学报,2012,32(28):27—35,22.[14]Yan Gangui, Feng Xiaodong, Li Jun, et al.Optimization of energy storage system capacity for relaxing peak load regulation bottlenecks[J].Proceedings of the CSEE,2012,32(28):27—35,22.
[15]高飞,杨凯,惠东,等.储能用磷酸铁锂电池循环寿命的能量分析[J].中国电机工程学报,2013,33(5):41—45,8.[15]Gao Fei,Yang Kai,Hui Dong,et al. Cycle-life energy analysis of LiFePO4batteries for rnergy storage[J].Proceedings of the CSEE,2013,33(5):41—45,8.
[16]Bindner H,Cronin T,Lundsager P,et al. Lifetime modelling of lead acid batteries[R]. Roskilde:Ris?National Laboratory,2005.
[2]熊雄,杨仁刚,叶林,等.电力需求侧大规模储能系统经济性评估[J].电工技术学报,2013,28(9):224—230.[2]Xiong Xiong,Yang Rengang,Ye Lin,et al. Economic evaluation of large-scale energy storage allocation in power demand side[J]. Transactions of China Electrotechnical Society,2013,28(9):224—230.
[3]刘冠群,袁越,王敏,等.考虑经济成本的光伏电站储能容量配置[J].可再生能源,2014,(1):1—5.[3]Liu Guanqun,Yuan Yue,Wang Min,et al. Energy storage capacity determining of PV plant considering economic cost[J]. Renewable Energy Resources,2014,(1):1—5.
[4]熊猛,高峰,张海峰,等.考虑调度计划的风电场复合储能装置优化设计[J].电网技术,2014,38(7):1853—1860.[4]Xiong Meng, Gao Feng, Zhang Haifeng, et al.Optimization design for hybrid energy storage device in wind farm taking scheduling into account[J]. Power System Technology,2014,38(7):1853—1860.
[5]娄素华,易林,吴耀武,等.基于可变寿命模型的电池储能容量优化配置[J].电工技术学报,2015,30(4):265—271.[5]Lou Suhua,Yi Lin,Wu Yaowu,et al. Optimizing deployment of battery energy storage based on lifetime predication[J]. Transactions of China Electrotechnical Society,2015,30(4):265—271.
[6]韩晓娟,田春光,张浩,等.用于削峰填谷的电池储能系统经济价值评估方法[J].太阳能学报,2014,35(9):1634—1638.[6]Han Xiaojuan,Tian Chunguang,Zhang Hao,et al.Economic evaluation method of battery energy storage system in peak load shifting[J]. Acta Energiae Solaris Sinica,2014,35(9):1634—1638.
[7]张国宝.储能影响未来能源大格局[J].中国电力企业管理,2015,(5):14—15.
[8]韩涛,卢继平,乔梁,等.大型并网风电场储能容量优化方案[J].电网技术,2010,34(1):169—173.[8]Han Tao,Lu Jiping,Qiao Liang. Optimized scheme of energy-storage capacity for grid-connected large-scale wind farm[J]. Power System Technology,2010,34(1):169—173.
[9]李碧辉,申洪,汤涌,等.风光储能联合发电系统储能容量对有功功率的影响及评价指标[J].电网技术,2011,35(4):123—128.[9]Li Bihui,Shen Hong,Tang Yong,et al. Impacts of energy storage capacity configuration of HPWS to active power characteristics and its relevant indices[J]. Power System Technology,2011,35(4):123—128.
[10]梁亮,李建林,惠东,等.大型风电场用储能装置容量的优化配置[J].高电压技术,2011,37(4):930—936.[10]Liang Liang,Li Jianlin,Hui Dong,et al. Optimization configuration for capacity of energy storage system in large-scale wind farm[J]. High Voltage Engineering,2011,37(4):930—936.
[11]冯江霞,梁军,张峰,等.考虑调度计划和运行经济性的风电场储能容量优化计算[J].电力系统自动化,2013,37(1):90—95.[11]Feng Jiangxia,Liang Jun,Zhang Feng,et al. An optimization calculation method of wind farm energy storage capacity[J]. Automation of Electric Power System,2013,37(1):90—95.
[12]姜书鹏,乔颖,徐飞,等.风储联合发电系统容量优化配置模型及敏感性分析[J].电力系统自动化,2013,37(20):16—21.[12]Jiang Shupeng,Qiao Ying,Xu Fei,et al. Capacity optimization and sensitivity analysis of cogeneration system of wind power and energy storage[J]. Automation of Electric Power Systems,2013,37(20):16—21.
[13]陆秋瑜,胡伟,闵勇,等.考虑时间相关性的风储系统多模式协调优化策略[J].电力系统自动化,2015,39(2):6—12.[13]Lu Qiuyu,Hu Wei,Min Yong,et al. A multi-pattern coordinated optimization strategy of wind power and energy storage system considering temporal dependence[J]. Automation of Electric Power System,2015,39(2):6—12.
[14]严干贵,冯晓东,李军徽,等.用于松弛调峰瓶颈的储能系统容量配置方法[J].中国电机工程学报,2012,32(28):27—35,22.[14]Yan Gangui, Feng Xiaodong, Li Jun, et al.Optimization of energy storage system capacity for relaxing peak load regulation bottlenecks[J].Proceedings of the CSEE,2012,32(28):27—35,22.
[15]高飞,杨凯,惠东,等.储能用磷酸铁锂电池循环寿命的能量分析[J].中国电机工程学报,2013,33(5):41—45,8.[15]Gao Fei,Yang Kai,Hui Dong,et al. Cycle-life energy analysis of LiFePO4batteries for rnergy storage[J].Proceedings of the CSEE,2013,33(5):41—45,8.
[16]Bindner H,Cronin T,Lundsager P,et al. Lifetime modelling of lead acid batteries[R]. Roskilde:Ris?National Laboratory,2005.